Advanced prediction of shipping attributes of a package in a dispensing pharmacy

ABSTRACT

Technologies are provided for advanced prediction of shipping attributes of a package in a dispensing pharmacy. In some embodiments, a computing system can receive prescription data identifying one or more amounts of respective medications, and can generate, using the prescription data, an estimate of weight of a package containing the one or more amounts of the respective medications. The computing system can then cause, at a time before automated packing of the respective medications into the package, a second computing system to provide shipping data for the package. The shipping data includes first data defining a shipping label. The second computing system can be remotely located relative to the computing system. The computing system can receive the shipping data at a second time before the automated packing of the respective medications into the package, and also can store the shipping data in a storage device.

SUMMARY

It is to be understood that both the following general description andthe following detailed description are illustrative and explanatory onlyand are not restrictive.

In one embodiment, the disclosure provides a computing system. Thecomputing system includes at least one processor; and at least onememory device having processor-executable instructions stored thereonthat, in response to execution by the at least one processor, cause thecomputing system to receive prescription data identifying one or moreamounts of respective medications; and generate, using the prescriptiondata, an estimate of weight of a package containing the one or moreamounts of the respective medications. The processor-executableinstructions, in response to execution by the at least one processor,also cause the computing system to cause, at a time before automatedpacking of the respective medications into the package, a secondcomputing system to provide shipping data for the package. The shippingdata comprises first data defining a shipping label. The secondcomputing system is remotely located relative to the computing system.The processor-executable instructions, in response to execution by theat least one processor, further cause the computing system to receivethe shipping data at a second time before the automated packing of therespective medications into the package; and store the shipping data ina storage device.

In another embodiment, the disclosure provides a computer-implementedmethod. The computer-implemented method includes receiving, by adispensing pharmacy system, prescription data identifying one or moreamounts of respective medications, and generating, by the dispensingpharmacy system, using the prescription data, an estimate of weight of apackage containing the one or more amounts of the respectivemedications. The computer-implemented method also includes causing, bythe dispensing pharmacy system, at a time before or during automatedpacking of the respective medications into the package, a secondcomputing system to provide shipping data for the package. The shippingdata comprises first data defining a shipping label. The secondcomputing system is remotely located relative to the dispensing pharmacysystem. The computer-implemented method further includes receiving theshipping data by the dispensing pharmacy system at a second time beforethe automated packing of the respective medications into the package;and storing, by the dispensing pharmacy system, the shipping data in astorage device.

In yet another embodiment, the disclosure provides a computer-programproduct. The computer-program product includes at least onecomputer-readable non-transitory storage medium havingprocessor-executable instructions stored thereon that, in response toexecution, cause a computing system to receive prescription dataidentifying one or more amounts of respective medications; and generate,using the prescription data, an estimate of weight of a packagecontaining the one or more amounts of the respective medications. Theprocessor-executable instructions, in response to execution, also causethe computing system to cause, at a time before automated packing of therespective medications into the package, a second computing system toprovide shipping data for the package. The shipping data comprises firstdata defining a shipping label. The second computing system is remotelylocated relative to the dispensing pharmacy system. Theprocessor-executable instructions, in response to execution, furthercause the computing system to receive the shipping data at a second timebefore the automated packing of the respective medications into thepackage; store the shipping data in a storage device.

Additional elements or advantages of this disclosure will be set forthin part in the description which follows, and in part will be apparentfrom the description, or may be learned by practice of the subjectdisclosure. The advantages of the subject disclosure can be attained bymeans of the elements and combinations particularly pointed out in theappended claims.

This summary is not intended to identify critical or essential featuresof the disclosure, but merely to summarize certain features andvariations thereof. Other details and features will be described in thesections that follow. Further, both the foregoing general descriptionand the following detailed description are illustrative and explanatoryonly and are not restrictive of the embodiments of this disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The annexed drawings are an integral part of the disclosure and areincorporated into the subject specification. The drawings illustrateexample embodiments of the disclosure and, in conjunction with thedescription and claims, serve to explain at least in part variousprinciples, elements, or aspects of the disclosure. Embodiments of thedisclosure are described more fully below with reference to the annexeddrawings. However, various elements of the disclosure can be implementedin many different forms and should not be construed as limited to theimplementations set forth herein. Like numbers refer to like elementsthroughout.

FIG. 1 illustrates an example of an operating environment for predictionof shipping attributes of a package and configuration of the package forshipping, in accordance with one or more embodiments of this disclosure.

FIG. 2 illustrates an example of an architecture of the operatingenvironment shown in FIG. 1 , in accordance with one or more embodimentsof this disclosure.

FIG. 3A illustrates an example of temporal order of a prediction stageand a packing stage for a package, in accordance with one or moreembodiments of this disclosure.

FIG. 3B illustrates another example of temporal order of a predictionstage and a packing stage for a package, in accordance with one or moreembodiments of this disclosure.

FIG. 4 illustrates an example of a process flow for prediction ofshipping attributes of a package and configuration of the package forshipping, in accordance with one or more embodiments of this disclosure.

FIG. 5 illustrates an example of a method for configuring a package forshipping, in accordance with one or more embodiments of this disclosure.

FIG. 6 illustrates an example of another operating environment that canimplement prediction of shipping attributes of a package andconfiguration of the package for shipping, in accordance with one ormore embodiments of this disclosure.

DETAILED DESCRIPTION

The disclosure recognizes and addresses, among other technicalchallenges, the issue of automated configuration of a package fordelivery from a dispensing pharmacy. Dispensing pharmacies, such as mailorder pharmacies, fill prescriptions for patients and ship thoseprescriptions directly to an address of the patients. In many cases thedispensing pharmacy can leverage one of an array of various shippingmethods (e.g., different carriers, different shipping durations, etc.).In order to select a satisfactory shipping method in terms of costand/or delivery time, the dispensing pharmacy can use a third-party rateservice. In existing technologies, the use of the third-party rateservice introduces undesirable delay within the packing process flowthat results in delivery of the package from the dispensing pharmacy.

Embodiments of this disclosure provide computing systems,computer-implemented methods, and computer program products that,individually or in combination, can eliminate such a delay. To that end,embodiments of the disclosure provide a prediction stage and a packingstage that are decoupled from one another. The prediction stage canprecede the packing stage and obtains shipping data, including anelectronic shipping label, from a rate service. Obtaining the shippingdata in the predictive stage can be referred to as “Advanced PredictiveManifesting,” for the sake of nomenclature. That shipping data isappropriate for a package containing prescribed medication(s) and/orprescribed supplies associated with at least one of the medication(s).The prescribed medication(s) can include tablets, capsules, liquids,unit-of-use packages, a combination thereof, or the like. The packingstage fills a package with the prescribed medication(s) and use theshipping data previously obtained in the prediction stage. Aftercontents of the package are verified the electronic shipping label canbe printed and applied to the package. The package is then released forsortation and shipping.

Although embodiments of this disclosure are described with reference toprescribed medications, the disclosure is not limited in that respect.Indeed, the principles and practical applications of this disclosurealso can be implemented for packages containing prescribed medicationsand supplies associated with one or more of the medications. Thus,embodiments of this disclosure can be implemented in cases where aprescription identifies a medication and one or more supplies associatedwith the medication. Supplies can include, for example, syringes or asharps container for safe disposal of syringes. In those cases, adispensing pharmacy can ship a package containing both the medicationand supplies to a patient. Advanced predictive manifesting in accordancewith this disclosure also can be implemented for such a package.

In sharp contrast to existing technologies, by decoupling interactionwith the rate service from the packing stage to fill, verify, and labela package for shipping, embodiments of this disclosure eliminate delayassociated with obtaining a shipping label for the package. As a result,interruption associated with communication with the rate service isabsent from a package verification and release step within a packingflow for a packing operator. Because such an interruption is absent,embodiments of this disclosure can perform such a packing flow withgreater efficiency than commonplace packing approaches. Accordingly, thegreater efficiency of embodiments of this disclosure can permit packinga larger number of packages per hour. Hence, a greater number ofpackages can be packed in a shift at the dispensing pharmacy or thenumber of human resources can be reduced for a same number of packagesper shift.

With reference to the drawings, FIG. 1 schematically illustrates anexample of an operating environment 100 for prediction of shippingattributes of a package and configuration of the package for shipping,in accordance with one or more embodiments of this disclosure. Theoperating environment 100 includes dispensing pharmacy devices 110 thatconstitute a dispensing pharmacy, such as a mail order pharmacy or a hubof a central-fill platform. The dispensing pharmacy has the licensure todispense medications, and also has an NPI number and an NCPDP processoridentification number (or BIN). The dispensing pharmacy devices 110 canperform automation processes to fulfill prescription fill requests andship a package containing one or multiple medications to a destinationaddress (e.g., a dwelling of a subject, a nursing home, anassisted-living facility, or similar). The prescription fill requestsinclude requests for new prescriptions and prescription refills. Asmentioned, while described in connection with medication(s), theoperating environment 100 also can be operated for prediction ofshipping attributes of a package containing one or more suppliesassociated with at least one medication also shipped within the package.

One of the dispensing pharmacy devices 110 can receive a prescriptionfill request 112 to be fulfilled. The prescription fill request 112 caninclude prescription data identifying one or more amounts of respectivemedications. The prescription data also can identify a shipping addressand/or a delivery deadline. An automation process to fulfill theprescription fill request 112 has an automation timeline 114 duringwhich a group of the dispensing pharmacy devices 110 can automaticallyperform several operations to package one or multiple medications into adelivery package 140 and to supply the delivery package 140 forshipment.

To implement such an automation process, as is illustrated in FIG. 2 ,the dispensing pharmacy devices 110 can include multiple subsystems 210and one or multiple gateways 240. At least one of the gateway(s) 240 canbe functionally coupled to one or more of the multiple subsystems 210. Agateway of the gateway(s) 240 can receive prescription fill requests andcan route the prescription fill requests to an intake subsystem includedin the multiple subsystems 210. Several of the subsystems 210 caninclude components that can implement an automation process to fulfill aprescription request. The subsystem 214 shown in FIG. 2 illustrates anexample of such subsystems. The subsystem 214 includes one or multipleserver devices 220 that can administer the automation process. Thesubsystems 214 also includes one or multiple memory devices 228 (whichcan be referred to as data storage 228). Although the data storage 228is illustrated as being external to the server device(s) 220, there areconfigurations where at least a portion of the data storage 228 isintegrated into at least one of the server device(s) 220. The subsystem214 further includes one or multiple control devices 224 and equipment232. The equipment 232 can include hoppers, conveyance systems, cameradevices, weight scales, radio-frequency identification (RFID) readerdevices, printing devices, and similar equipment. The control device(s)224 can control the operation of at least some of the equipment 232 inorder to execute the automation process. A bus architecture (representedby connected arrows) permit exchanging data and/or signaling among theserver device(s) 220, the control device(s) 224, the equipment 232, andthe data storage 228.

With further reference to FIG. 1 , a gateway (not depicted) can receivethe prescription fill request 112 at an intake time t_(in). The gatewaycan route the prescription fill request 112 to a server device (e.g.,one of the server device(s) 220 (FIG. 2 )). Using the prescription datawithin the prescription fill request 112, the server device can generatean estimate of weight of a package containing the one or more amounts ofrespective medications identified by the prescription data. That serverdevice can be referred to as a predictor server device.

To generate the estimate of the weight of the package, the predictorserver device can identify one or more receptacles suitable to fit theamount(s) of the respective medications identified by the prescriptiondata. Identifying the receptacle(s) can include determining one or moretypes of receptacles and number of receptacle(s). The predictor serverdevice can then access a database, for example, to determine respectiveweights of the one or more types of receptacles. For each type ofreceptacle that has been determined, the predictor server device canthen determine a net weight of one or more receptacles of a particulartype. In addition, based on the medication(s) identified in theprescription data, the predictor server device also can access thedatabase to identify a weight of a capsule or tablet and/or a specificweight of a liquid. The predictor server device can then determine a netweight of tablets, capsules, and/or liquids corresponding to one or moreamounts of respective medications. In case of a liquid, the amount ofmedication can be prescribed in terms of a volume. The net weight of theprescribed amount of liquid can be determined using the specific weightof the liquid and the volume. In scenarios where the prescription datawithin the prescription fill request 112 includes data identifying oneor more unit-of-use packages, the predictor server device can determinea net weight of the unit-of-use package(s) by accessing the database todetermine respective weights of the prescribed unit-of-use package(s). Aunit-of-use package can include, for example, a blister pack, ametered-dose inhaler, a course-of-therapy vial, or the like. Theprescribed unit-of-use-packages can be of the same type (e.g., twometered-dose inhalers) or can include a combination of packages ofdifferent types (e.g., a metered-dose inhaler and a blister pack).Further, the predictor server device also includes other weights to theestimate, such as the weight of the material that forms the package, andin some cases, weight of packing elements that may be present in thepackage for purposes of preserving the contents of the package in adesired state and/or providing stability. Hence, in some cases, thepredictor server device can generate the estimate of the weight of thepackage containing the one or more amounts of respective medications byadding the net weight of the one or more receptacles of a particulartype, for each type; the net weight of tablets, capsules, and/or liquidscorresponding to one or more amounts of respective medications; and theweight of the package without prescribed contents (that is, weight of abox and weight of packing element(s) within the box, for example). Incases where one or more unit-of-use packages are prescribed instead of,or in addition to, other types of medications, the predictor serverdevice can add the net weight of the unit-of-use package(s) to theestimate of the weight of the package.

By generating the estimate of the weight of the package and havingaccess to other shipping attributes corresponding to the prescriptionfill request 112, the predictor server device can search for asatisfactory shipping service in terms of satisfactory cost and deliverytimeframe to ship the delivery package 140. To that end, the predictorserver device can use a rate service. The rate service can be acloud-hosted service, in some embodiments, and can be provided by rateservice devices 130. As is illustrated in FIG. 1 , the rate servicedevices 130 can be remotely located relative to the dispensing pharmacy.The rate service devices 130 can include a rate service server 134 thatcan determine a solution to a rate search problem with respect to theestimated weight of the package and one or more other shippingattributes corresponding to the shipping package. Solving such a ratesearch problem can determine a satisfactory shipping provider amongstvarious shipping providers.

A solution to that rate search problem defines shipping datacorresponding to the satisfactory shipping service. The shipping datacan define one or multiple shipping attributes. As such, the shippingdata can include first data defining an electronic shipping label for adesired package to be delivered. As is illustrated in FIG. 2 , the rateservice devices 130 can include multiple subsystems 250 and one or moregateways 260. A subsystem 254 can include the rate service server 134.In some embodiments, more than one of the subsystems 250 can include therate service server 134.

Referring again to FIG. 1 , to obtain shipping data for the packagecontaining the one or more medications identified by the prescriptionfill request 112, the predictor server device can cause the rate serviceserver 134 to provide such shipping data. To that end, the predictorserver device can establish a call session with the rate service server134 at a time t_(i) before automated packing of the one or moremedications into the package 140. Upon establishing the call session, orafter the call session has been established, the predictor server devicecan send, via the call session, a query message 118 for the shippingdata to the rate service server 134. One or more networks 120 can permitestablishing the session call and transporting the query message 118 toa gateway that can route the query message to rate service server 134.The network(s) 120 can include wireless network(s), wireline network(s),or a combination of such networks.

The query message 118 can include payload data identifying shippingattributes corresponding to the package 140. The shipping attributes caninclude one or a combination of a first attribute identifying theestimate of the weight of the package 140, a second attributeidentifying the respective medications, a third attribute identifying ashipping address, or a fourth attribute identifying a delivery deadline.

The rate service server 134 can determine a solution to the rate searchproblem to determine a satisfactory shipping provider amongst variousshipping providers. That solution includes shipping data requested forthe package 140. In response to determining such a solution, the rateservice server 134 can send a response message 136 to the predictorserver device, where the response message 136 includes the shippingdata. To that end, the rate service server 134 can route the responsemessage 136 via a gateway (e.g., one of the gateway(s) 260) that cansend the response message 136 to the predictor server device via thenetwork(s) 120.

The predictor server device can receive the response message 136, andthe shipping data therein, at a time t_(f) after t_(i) and still beforethe automated packing of the one or more medications into the package140. The magnitude of the time interval t_(f)-t_(i) to obtain theresponse message 136 can depend on various factors, such as networktraffic, network bandwidth, or the like. In some cases the time intervalt_(f)-t_(i) can span several seconds (e.g., 5 s, 10 s, 15 s). Theresponse message 136 can be received by means of a pharmacy gateway (oneof the gateway(s) 240 (FIG. 2 ), for example).

In response to receiving the response message 136, the predictor serverdevice can store the shipping data in a data repository (e.g., datastorage 228 (FIG. 2 )). In some embodiments, the data repository can beintegrated into a pharmacy server device that can administer theautomated packing of medications within the dispensing pharmacy. In oneexample, that pharmacy server device can be embodied in one of theserver device(s) 220. In other embodiments, the data repository can befunctionally coupled to that pharmacy server device such that latencyfor data transfer between the pharmacy server device and the datarepository can be maintained within a satisfactory level. Configurationshaving latency that is less than or similar to two seconds can providesatisfactory data transfer between the pharmacy server device and thedata repository.

By receiving the response message 136, data defining a shipping labelfor the package 140 become available to the dispensing pharmacy system.Thus, the shipping label can be ready to be printed and applied to thepackage 140, without further communication across the network(s) 120,after completion of the automated packing of the one or more medicationsinto the package 140. It is noted that the advanced predictivemanifesting also can be applied to other packing modalities, such assemi-automated packing. Those other modalities also can benefit from theshipping label being ready to be printed and applied to the package 140.

The pharmacy server device that administers the automated packing ofmedications can initiate the automated packing of the one or moreamounts of respective medications identified by the prescription fillrequest. Such an automated packing can be initiated at a time t_(p)after t_(f). The automated packing of the one or more amounts ofrespective medications can proceed until a completion time t_(pck) whenthe assembly of the package 140 is complete. After such a completiontime, the assembled package 140 can be verified for shipping.

In response to being verified, the pharmacy server device can receive anotification (an interrupt signal, for example) that the package isverified for shipping. The notification can be received after theautomated packing of the one or more amounts of respective medicationsinto the package 140 is complete. The pharmacy server device can thenaccess the shipping data from the data repository in response toreceiving the notification. In embodiments in which the data repositoryis integrated into the pharmacy server device, the pharmacy serverdevice can receive the notification and can then read the shipping datafrom the data repository.

Receiving the shipping data can cause the pharmacy server device todirect a printing device (not depicted in FIG. 1 ) to output theshipping label 150. Outputting the shipping label 150 includes printingindicia defining the shipping label on a solid medium. The printingdevice can be embodied in, for example, a thermal printer configured toprint single-size labels or multi-size labels. The time at which theshipping label 150 is printed is denoted by t_(print) in FIG. 1 . Aftert_(print), the shipping label 150 can be applied to the package 140. Thelabeled package 140 can then be released for transportation to sortationequipment and a shipping bay for subsequent shipping. For instance, thelabeled package 140 can be released to conveyance equipment that canmove the labeled packaged 140 to the sortation equipment and shippingbay. The labeled package 140 can then be shipped to a patient 160. InFIG. 1 , shipping is depicted with a straight arrow towards the patient150.

In an example scenario, the notification can be embodied in an interruptsignal that causes the pharmacy server device to read the shipping datafor the package 140. The result signal can be generated by a peripheraldevice integrated into or otherwise coupled to the pharmacy serverdevice. In some cases, the peripheral device can be a touch-screendisplay device and the result signal can be generated in response to atouch of a selectable user-interface element the represents a verifiedcondition of a package. After reading the shipping data, the pharmacyserver device can cause the printing device to output the shipping label150 using the shipping data.

In sharp contrast to existing technologies, because shipping datadefining the shipping label 150 is obtained before filling the package140 with one or multiple medications, verification of package contentsand generation of the shipping label 150 can proceed without delayassociated with obtaining shipping data defining the shipping label 150.In other words, the time interval t_(f)-t_(i) elapsed when obtaining theshipping data defining the shipping label 150 can be avoided after thepackage 150 has been filled with the one or several medicationsidentified by the prescription fill request 112. As a result, theefficiency of the packing process flow to fill and label the package 140can be improved relative to existing packing approaches.

FIG. 3A summarizes the temporal order of a prediction stage 310 and apacking stage 320, in accordance with one or more embodiments of thisdisclosure. During the prediction stage 310, the predictor serverdevice, or another server device of the dispensing pharmacy, cangenerate of estimate of weight of a package containing one or moreamounts of respective medications. In addition, a pharmacy server deviceor another server device of the dispensing pharmacy, can obtain datadefining a shipping label for the package and other data defining othershipping attributes for the package. As is described herein, theprediction stage 310 can span a time interval t_(f)-t_(i) (see FIG. 1 ).It is noted that the prediction stage also can be applied to a packagecontaining one or more supplies associated with a medication alsoshipped within the package.

The prediction stage 310 precedes the packing stage 320. The packingstage 320 can be implemented according to one of various packingmodalities, such as automated packing and semi-automated packing. Insome cases, a particular packing modality of the packing modalities mayinclude an agent performing the assembly of the package. The agent canbe a human operator or an autonomous apparatus. The autonomous apparatuscan be embodied in an automated computing device that implementsmachine-learning techniques in order to make autonomous inferences basedon various types of input data, including video data, audio data,structured data, unstructured data, a combination thereof, or similarinformation.

In some embodiments, in the packing stage 320, automation controldevices can control various equipment within the dispensing pharmacythat, as mentioned, can implement an automated packing process to fill apackage with one or more multiple medications. Regardless of packingmodality, the packing stage 320 includes a verification and release step330 (represented with a hatched block in FIG. 3A) where the contents ofthe package can be verified and a shipping label (e.g., shipping label150 can be generated prior to the package being released for shipping.As mentioned, because the prediction stage 310 yields data defining theshipping label, the verification and release step 330 in embodiments ofthis disclosure can proceed without interruption associated withobtaining shipping data defining the shipping label for the package.

The verification and release step 330 can include automaticallydetermining a difference between the estimate of the weight of thepackage assembled during an earlier portion of the packing stage 320 andan actual weight of the package. Accordingly, automatically determiningsuch a difference can include, for example, routing the package to aweigh scale, positioning the package on the weight scale, obtaining oneor more measurements of the weight of the package, and moving thepackage from weight scale. Additionally, automatically determining sucha difference can include comparing the measured weight to the estimateof the weight. In some cases, such a comparison can indicate that amagnitude of the difference between the measured weight and theestimated weight exceeds a defined tolerance. The tolerance can bedefined as a particular threshold weight (e.g., 1 g, 2 g, 5 g, 10 g, or15 g) or a threshold percentage change (e.g., 0.5%, 1%, or 2%). Hence,in those cases, the package can be deemed to be unverified, and one ormultiple exception handling operations can be performed. For example,the exception handling operation(s) can include routing the package forspecial handling by a packing agent (e.g., human operator or anautonomous apparatus) to re-do the shipping rate determination, shippingmethod selection, and shipping label generation and application. Inother cases, such a comparison can indicate that a magnitude of thedifference between the measured weight and the estimated weight is lessthan or equal to the defined tolerance. In those cases, the package isdeemed to be verified.

In some situations, the prediction stage 310 and the packing stage 320may partially overlap in time domain. For instance, as is illustrated inFIG. 3B, in cases where the time spanned to complete the automatedpacking of one or more medications into a package is greater than thetime interval t_(f)-t_(i), the automated packing can be initiated beforethe prediction stage has been completed.

FIG. 4 illustrates an example of a process flow for prediction ofshipping attributes of a package and configuration of the package forshipping, in accordance with one or more embodiments of this disclosure.The pharmacy server device 410, the data storage 420, and the predictorserver device 430 constitute a dispensing pharmacy system. The predictorserver device 430 can receive the prescription fill request 112 at anintake time. Using the prescription data within the prescription fillrequest 112, the predictor server device 430 can perform an estimateprocess 434 that generates an estimate of weight of a package containingthe one or more amounts of respective medications identified by theprescription data.

The predictor server device 430 can cause the rate service server 134 toprovide such shipping data. To that end, the predictor server device 430can establish a call session with the rate service server 134 at a timebefore automated packing of the one or more medications into thepackage. The predictor server device 430 can send, via the call session,the query message 118 to the rate service server 134.

The rate service server 134 can implement a search process 438 thatdetermines a solution to a rate search problem with respect to theestimated weight of the package and one or more other shippingattributes corresponding to the shipping package. Such a solutiondefines shipping data corresponding to the satisfactory shippingservice. The shipping data can define one or multiple shippingattributes. Accordingly, the shipping data can include first datadefining an electronic shipping label for the package containing the oneor more amounts of respective medications. In response to determiningsuch a solution, the rate service server 134 can send the responsemessage 136 to the predictor server device 430, where the responsemessage 136 includes the shipping data.

The predictor server device 430 can receive the response message 136,and the shipping data therein, at a second time before the automatedpacking of the one or more medications into the package has beencompleted. In response to receiving the response message 136, thepredictor server device 430 can store the shipping data in data storage420. One or multiple storage devices can constitute the data storage420. Similar to the data storage 228 (FIG. 2 ), the data storage 420 canbe integrated into or otherwise functionally coupled to the pharmacyserver device 410 such that latency for data transfer between thepharmacy server device and the data storage 420 can be maintained withina satisfactory level.

Although the pharmacy server device 410 also receives the prescriptionfill request 112 essentially at the intake time, the pharmacy serverdevice 410 defers the execution of the automated packing process untilafter the predictor server device 430 has obtained the response message136 and retained the shipping data within the data storage 420.

Accordingly, after the predictor server device 430 retains the responsemessage within the data storage 420, the pharmacy server device 410 caninitiate the automated packing of the one or more amounts of respectivemedications identified by the prescription fill request 112. Asmentioned, the automated packing of the one or more amounts ofrespective medications can proceed until a completion time (e.g.,t_(pck)) when the assembly of the package is complete. It is noted that,in some configurations, as is described in connection with FIG. 3B, theautomated packing is not deferred and can be initiated prior to theresponse message being retained in the data storage 420.

After such a completion time, the assembled package 140 can be verifiedfor shipping. Verification can include automatically determining adifference between the estimate of the weight of the assembled package140 and the actual weight of the assembled package 140, in accordancewith aspects described hereinbefore in connection with step 330 (FIG. 3Aand FIG. 3B). An accuracy that exceeds a defined tolerance indicatesthat the assembled package 140 can be deemed unverified. In response tobeing unverified, one or more exception handling operations can beimplemented, as is described herein. In turn, an accuracy that is lessthan or equal to a defined tolerance, indicates that can be deemed to beverified.

In response to the assembled package 140 being verified, the pharmacyserver device 410 can receive a notification 440 (such as an interruptsignal) that the package is verified for shipping. The pharmacy serverdevice 410 can then access the shipping data from the data storage 420.The pharmacy server device 410 can send, to the data storage 420, arequest message (such as a control message) for a portion of theshipping data that defines a shipping label for the package. Inresponse, the pharmacy server device 410 can supply a response message442 that includes payload data defining the shipping label.

Receiving the response message 442 can cause the pharmacy server device410 to direct a printing device 450 to output the shipping label. Todirect the printing device 450 to output the shipping label, thepharmacy server device 410 can send an instruction message 446 havingthe payload data defining the shipping label. Outputting the shippinglabel includes printing indicia defining the shipping label on a solidmedium 460. Thus, the printed solid medium 460 embodies the shippinglabel. The printing device 450 can be embodied in, for example, athermal printer or a laser printer configured to print single-sizelabels or multi-size labels. The printed solid medium 460 can beconfigured to be applied to a surface of the package containing the oneor more amounts of respective medications identified by the prescriptionfill request 112. After the solid medium 460 has been applied to thepackage 140, the labeled package 140 can then be released for shipping.

FIG. 5 illustrates an example of a method 500 for configuring a packagefor shipping, in accordance with one or more embodiments of thisdisclosure. The example method 500 includes operations pertaining topredicting shipping attributes of the package and preparing the packagefor release to conveyance mechanisms that can transport to the packageto a shipping bay or similar apparatus in preparation for delivery.While the example method 500 is illustrated with reference to shippingof medications, the disclosure is not limited in that respect. Indeed,the principles and practical applications of this disclosure can bedirected to other types items permitted for shipping or otherwiseavailable for shipping from a dispensing pharmacy. For instance, theexample method 500 also can be implemented for shipping of a medicationand one or more supplies associated with the medication.

A computing system can perform the example method 500 in its entirety orin part. To that end, the computing system includes computing resourcesthat can implement at least one of the blocks included in the examplemethod 500. The computing resources include, for example, centralprocessing units (CPUs), graphics processing units (GPUs), tensorprocessing units (TPUs), memory, disk space, incoming bandwidth, and/oroutgoing bandwidth, interface(s) (such as I/O interfaces or APIs, orboth); controller devices(s); power supplies; a combination of theforegoing; and/or similar resources. For instance, the computing systemcan include programming interface(s); an operating system; software forconfiguration and or control of a virtualized environment; firmware; andsimilar resources. In some embodiments, the computing system can embody,or can include, one or a combination of the predictor server device 430,the data storage 420, or the pharmacy server device 410 (FIG. 4 ). Thecomputing system can be integrated into a dispensing pharmacy and, thus,can be referred to as a dispensing pharmacy system.

At block 510, the dispensing pharmacy system can receive prescriptiondata identifying one or more amounts of respective medications. Theprescription data can be contained in a prescription fill request tofill or refill a prescription.

At block 520, the dispensing pharmacy system can generate an estimate ofweight of a package containing the one or more amounts of the respectivemedications. Such an estimate can be generated using the prescriptiondata. In some embodiments, as is described herein, generating theestimate of the weight can include identifying a receptacle to fit afirst amount of the one or more amounts of respective medications, anddetermining a weight of the identified receptacle by accessing adatabase including a catalogue of receptacles. Generating the estimateof weight also can include determining a weight of the first amount ofthe one or more amounts of respective medications. Additionally,generating the estimate of the weight further includes adding a weightof the package without prescribed content but including, as applicable,one or more packing elements; the weight of the identified receptacle;and the weight of the first amount of the one or more amounts ofrespective medications.

As mentioned, in some embodiments, the prescription data can identifyone or more unit-of-use packages. Thus, generating the estimate of theweight can include determining respective weights of the unit-of-usepackage(s) and adding the respective weights to the estimate.

At block 530, the dispensing pharmacy system can cause, at a time beforeor during automated packing of the respective medications, a computingsystem to provide shipping data for the package. The shipping data candefine one or multiple shipping attributes. A portion of the shippingdata includes first data defining an electronic shipping label. Thecomputing system can be remotely located relative to the dispensingpharmacy system. In some embodiments, the computing system can beembodied in, or can include, the rate service server 134 (FIG. 1 ). Insome embodiments, causing the computing system to provide the shippingdata can include establishing a call session with the computing system,and sending, via the call session, a query message for the shipping datato the computing system. The query message can include payload dataidentifying shipping attributes corresponding to the delivery package.The shipping attributes can include one or a combination of a firstshipping attribute identifying the estimate of the weight of thedelivery package, a second shipping attribute identifying the respectivemedications, a third shipping attribute identifying a shipping address,or a fourth shipping attribute identifying a delivery deadline.

At block 540, the dispensing pharmacy system can receive the shippingdata. The shipping data can be received by means of a pharmacy gateway(one of the gateways 240 (FIG. 2 ), for example).

At block 550, the dispensing pharmacy system can store the shipping datain a data repository (e.g., data storage 228 (FIG. 2 )). As is describedherein, in some embodiments, the data repository can be integrated intoa server device that can administer the automated packing of medicationswithin the dispensing pharmacy. In other embodiments, the datarepository can be functionally coupled to that server device such thatlatency for data transfer between the server device and the datarepository can be maintained within a satisfactory level.

At block 560, the dispensing pharmacy system can receive a notificationthat the package is verified for shipping. The notification can bereceived at a second time after the automated packing of the respectivemedications into the package. At block 570, the dispensing pharmacysystem can access the shipping data from the data repository. Inembodiments in which the data repository is integrated into the serverdevice that can administer the automated packing of medications withinthe dispensing pharmacy, that server device receive the notification andcan read the shipping data from the data repository.

At block 580, the dispensing pharmacy system can cause a printing deviceto output the shipping label on a solid medium. The printing device canbe embodied in, for example, a thermal printer configured to printsingle-size labels or multi-size labels. In one example, the printingdevice can be embodied in the printing device 450 (FIG. 4 ) and theshipping label can be embodied in the shipping label 460 (FIG. 2 ).

In order to provide some context, the computer-implemented method andsystems of this disclosure can be implemented on the computingenvironment illustrated in FIG. 6 and described below. Similarly, thecomputer-implemented methods and systems disclosed herein can utilizeone or more computing devices to perform one or more functions in one ormore locations. FIG. 6 is a block diagram illustrating an example of acomputing environment 600 for performing the disclosed methods and/orimplementing the disclosed systems. The computing environment 600 shownin FIG. 6 is only an example of an operating environment and is notintended to suggest any limitation as to the scope of use orfunctionality of operating environment architecture. Neither should theoperating environment be interpreted as having any dependency orrequirement relating to any one or combination of components illustratedin the exemplary operating environment. The computing environment 600shown in FIG. 6 can embody at least a portion of the operatingenvironment 100 (FIG. 1 ) or the architecture shown in FIG. 2 , and canimplemented the various functionalities described herein connection withadvanced predictive manifesting, For example, a portion of the computingenvironment 600 can embody the predictor server device 430, the datastorage 420, the pharmacy server device 410, and can operate inaccordance with aspects described herein. Such a portion of thecomputing environment 600 can be integrated into a dispensing pharmacy,for example, and thus, can be referred to as a dispensing pharmacysystem. A portion of the computing environment 600 also can include therate service server 134.

The computer-implemented methods and systems in accordance with thisdisclosure can be operational with numerous other general purpose orspecial purpose computing system environments or configurations.Examples of well-known computing systems, environments, and/orconfigurations that can be suitable for use with the systems and methodscomprise, but are not limited to, personal computers, server computers,laptop devices, and multiprocessor systems. Additional examples compriseset-top boxes, programmable consumer electronics, network PCs,minicomputers, mainframe computers, distributed computing environmentsthat comprise any of the above systems or devices, and the like.

The processing of the disclosed computer-implemented methods and systemscan be performed by software components. The disclosed systems andcomputer-implemented methods can be described in the general context ofcomputer-executable instructions, such as program modules, beingexecuted by one or more computers or other devices. Generally, programmodules comprise computer code, routines, programs, objects, components,data structures, etc. that perform particular tasks or implementparticular abstract data types. The disclosed methods can also bepracticed in grid-based and distributed computing environments wheretasks are performed by remote processing devices that are linked througha communications network. In a distributed computing environment,program modules can be located in both local and remote computer storagemedia including memory storage devices.

Further, one skilled in the art will appreciate that the systems andcomputer-implemented methods disclosed herein can be implemented via ageneral-purpose computing device in the form of a computing device 601.The components of the computing device 601 can comprise, but are notlimited to, one or more processors 603, a system memory 612, and asystem bus 613 that couples various system components including the oneor more processors 603 to the system memory 612. The system can utilizeparallel computing.

The system bus 613 represents one or more of several possible types ofbus structures, including a memory bus or memory controller, aperipheral bus, an accelerated graphics port, or local bus using any ofa variety of bus architectures. The bus 613, and all buses specified inthis description can also be implemented over a wired or wirelessnetwork connection and each of the subsystems, including the one or moreprocessors 603, a mass storage device 604, an operating system 605,software 606, data 607, a network adapter 608, the system memory 612, anInput/Output Interface 610, a display adapter 609, a display device 611,and a human-machine interface 602, can be contained within one or moreremote computing devices 614 a,b,c at physically separate locations,connected through buses of this form, in effect implementing a fullydistributed system.

The computing device 601 typically comprises a variety ofcomputer-readable media. Exemplary readable media can be any availablemedia that is accessible by the computing device 601 and comprises, forexample and not meant to be limiting, both volatile and non-volatilemedia, removable and non-removable media. The system memory 612comprises computer readable media in the form of volatile memory, suchas random access memory (RAM), and/or non-volatile memory, such as readonly memory (ROM). The system memory 612 typically contains data such asthe data 607 and/or program modules such as the operating system 605 andthe software 606 that are immediately accessible to and/or are presentlyoperated on by the one or more processors 603.

In another aspect, the computing device 601 can also comprise otherremovable/non-removable, volatile/non-volatile computer storage media.By way of example, FIG. 6 illustrates the mass storage device 604 whichcan provide non-volatile storage of computer code, computer readableinstructions, data structures, program modules, and other data for thecomputing device 601. For example and not meant to be limiting, the massstorage device 604 can be a hard disk, a removable magnetic disk, aremovable optical disk, magnetic cassettes or other magnetic storagedevices, flash memory cards, CD-ROM, digital versatile disks (DVD) orother optical storage, random access memories (RAM), read only memories(ROM), electrically erasable programmable read-only memory (EEPROM), andthe like.

Optionally, any number of program modules can be stored on the massstorage device 604, including by way of example, the operating system605 and the software 606. Each of the operating system 605 and thesoftware 606 (or some combination thereof) can comprise elements of theprogramming and the software 606. The data 607 can also be stored on themass storage device 604. The data 607 can be stored in any of one ormore databases known in the art. Examples of such databases comprise,DB2®, Microsoft® Access, Microsoft® SQL Server, Oracle®, mySQL,PostgreSQL, and the like. The databases can be centralized ordistributed across multiple systems.

In another aspect, the user can enter commands and information into thecomputing device 601 via an input device (not shown). Examples of suchinput devices comprise, but are not limited to, a keyboard, pointingdevice (e.g., a “mouse”), a microphone, a joystick, a scanner, tactileinput devices such as gloves, and other body coverings, and the likeThese and other input devices can be connected to the one or moreprocessors 603 via the human-machine interface 602 that is coupled tothe system bus 613, but can be connected by other interface and busstructures, such as a parallel port, game port, an IEEE 1394 Port (alsoknown as a Firewire port), a serial port, or a universal serial bus(USB).

In yet another aspect, the display device 611 can also be connected tothe system bus 613 via an interface, such as the display adapter 609. Itis contemplated that the computing device 601 can have more than onedisplay adapter 609 and the computing device 601 can have more than onedisplay device 611. For example, the display device 611 can be amonitor, an LCD (Liquid Crystal Display), or a projector. In addition tothe display device 611, other output peripheral devices can comprisecomponents such as speakers (not shown) and a printer (not shown) whichcan be connected to the computing device 601 via the Input/OutputInterface 610. Any operation and/or result of the methods can be outputin any form to an output device. Such output can be any form of visualrepresentation, including, but not limited to, textual, graphical,animation, audio, tactile, and the like. The display device 611 andcomputing device 601 can be part of one device, or separate devices.

The computing device 601 can operate in a networked environment usinglogical connections to one or more remote computing devices 614 a,b,c.By way of example, a remote computing device can be a personal computer,portable computer, smartphone, a server, a router, a network computer, apeer device or other common network node, and so on. Logical connectionsbetween the computing device 601 and a remote computing device 614 a,b,ccan be made via a network 615, such as a local area network (LAN) and/ora general wide area network (WAN). Such network connections can bethrough the network adapter 608. The network adapter 608 can beimplemented in both wired and wireless environments. In an aspect, oneor more of the remote computing devices 614 a,b,c can comprise anexternal engine and/or an interface to the external engine.

For purposes of illustration, application programs and other executableprogram components such as the operating system 605 are illustratedherein as discrete blocks, although it is recognized that such programsand components reside at various times in different storage componentsof the computing device 601, and are executed by the one or moreprocessors 603 of the computer. An implementation of the software 606can be stored on or transmitted across some form of computer-readablemedia. Any of the disclosed methods can be performed by computerreadable instructions embodied on computer-readable media.Computer-readable media can be any available media that can be accessedby a computer. By way of example and not meant to be limiting,computer-readable media can comprise “computer storage media” and“communications media.” “Computer storage media” comprise volatile andnon-volatile, removable and non-removable media implemented in anymethods or technology for storage of information such ascomputer-readable instructions, data structures, program modules, orother data. Exemplary computer storage media comprises, but is notlimited to, RAM, ROM, EEPROM, flash memory or other memory technology,CD-ROM, digital versatile disks (DVD) or other optical storage, magneticcassettes, magnetic tape, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to store thedesired information and which can be accessed by a computer.

It is to be understood that the methods and systems described here arenot limited to specific operations, processes, components, or structuredescribed, or to the order or particular combination of such operationsor components as described. It is also to be understood that theterminology used herein is for the purpose of describing exemplaryembodiments only and is not intended to be restrictive or limiting.

As used herein the singular forms “a,” “an,” and “the” include bothsingular and plural referents unless the context clearly dictatesotherwise. Values expressed as approximations, by use of antecedentssuch as “about” or “approximately,” shall include reasonable variationsfrom the referenced values. If such approximate values are included withranges, not only are the endpoints considered approximations, themagnitude of the range shall also be considered an approximation. Listsare to be considered exemplary and not restricted or limited to theelements comprising the list or to the order in which the elements havebeen listed unless the context clearly dictates otherwise.

Throughout the specification and claims of this disclosure, thefollowing words have the meaning that is set forth: “comprise” andvariations of the word, such as “comprising” and “comprises,” meanincluding but not limited to, and are not intended to exclude, forexample, other additives, components, integers, or operations. “Include”and variations of the word, such as “including” are not intended to meansomething that is restricted or limited to what is indicated as beingincluded, or to exclude what is not indicated. “May” means somethingthat is permissive but not restrictive or limiting. “Optional” or“optionally” means something that may or may not be included withoutchanging the result or what is being described. “Prefer” and variationsof the word such as “preferred” or “preferably” mean something that isexemplary and more ideal, but not required. “Such as” means somethingthat serves simply as an example.

Operations and components described herein as being used to perform thedisclosed methods and construct the disclosed systems are illustrativeunless the context clearly dictates otherwise. It is to be understoodthat when combinations, subsets, interactions, groups, etc. of theseoperations and components are disclosed, that while specific referenceof each various individual and collective combinations and permutationof these may not be explicitly disclosed, each is specificallycontemplated and described herein, for all methods and systems. Thisapplies to all aspects of this application including, but not limitedto, operations in disclosed methods and/or the components disclosed inthe systems. Thus, if there are a variety of additional operations thatcan be performed or components that can be added, it is understood thateach of these additional operations can be performed and componentsadded with any specific embodiment or combination of embodiments of thedisclosed systems and methods.

Embodiments of this disclosure may take the form of an entirely hardwareembodiment, an entirely software embodiment, or an embodiment combiningsoftware and hardware aspects. Furthermore, the methods and systems maytake the form of a computer program product on a computer-readablestorage medium having computer-readable program instructions (e.g.,computer software) embodied in the storage medium. Any suitablecomputer-readable storage medium may be utilized including hard disks,CD-ROMs, optical storage devices, or magnetic storage devices, whetherinternal, networked, or cloud-based.

Embodiments of this disclosure have been described with reference todiagrams, flowcharts, and other illustrations of computer-implementedmethods, systems, apparatuses, and computer program products. Each blockof the block diagrams and flowchart illustrations, and combinations ofblocks in the block diagrams and flowchart illustrations, respectively,can be implemented by processor-accessible instructions. Suchinstructions can include, for example, computer program instructions(e.g., processor-readable and/or processor-executable instructions). Theprocessor-accessible instructions can be built (e.g., linked andcompiled) and retained in processor-executable form in one or multiplememory devices or one or many other processor-accessible non-transitorystorage media. These computer program instructions (built or otherwise)may be loaded onto a general-purpose computer, special purpose computer,or other programmable data processing apparatus to produce a machine.The loaded computer program instructions can be accessed and executed byone or multiple processors or other types of processing circuitry. Inresponse to execution, the loaded computer program instructions providethe functionality described in connection with flowchart blocks(individually or in a particular combination) or blocks in blockdiagrams (individually or in a particular combination). Thus, suchinstructions which execute on the computer or other programmable dataprocessing apparatus create a means for implementing the functionsspecified in the flowchart blocks (individually or in a particularcombination) or blocks in block diagrams (individually or in aparticular combination).

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including processor-accessibleinstruction (e.g., processor-readable instructions and/orprocessor-executable instructions) to implement the function specifiedin the flowchart blocks (individually or in a particular combination) orblocks in block diagrams (individually or in a particular combination).The computer program instructions (built or otherwise) may also beloaded onto a computer or other programmable data processing apparatusto cause a series of operations to be performed on the computer or otherprogrammable apparatus to produce a computer-implemented process. Theseries of operations can be performed in response to execution by one ormore processor or other types of processing circuitry. Thus, suchinstructions that execute on the computer or other programmableapparatus provide operations for implementing the functions specified inthe flowchart blocks (individually or in a particular combination) orblocks in block diagrams (individually or in a particular combination).

Accordingly, blocks of the block diagrams and flowchart illustrationssupport combinations of means for performing the specified functions inconnection with such diagrams and/or flowchart illustrations,combinations of operations for performing the specified functions andprogram instruction means for performing the specified functions. Eachblock of the block diagrams and flowchart illustrations, andcombinations of blocks in the block diagrams and flowchartillustrations, can be implemented by special purpose hardware-basedcomputer systems that perform the specified functions or operations, orcombinations of special purpose hardware and computer instructions.

The methods and systems can employ artificial intelligence techniquessuch as machine learning and iterative learning. Examples of suchtechniques include, but are not limited to, expert systems, case-basedreasoning, Bayesian networks, behavior-based AI, neural networks, fuzzysystems, evolutionary computation (e.g. genetic algorithms), swarmintelligence (e.g. ant algorithms), and hybrid intelligent systems (e.g.expert inference rules generated through a neural network or productionrules from statistical learning).

While the computer-implemented methods, apparatuses, devices, andsystems have been described in connection with preferred embodiments andspecific examples, it is not intended that the scope be limited to theparticular embodiments set forth, as the embodiments herein are intendedin all respects to be illustrative rather than restrictive.

Unless otherwise expressly stated, it is in no way intended that anymethod set forth herein be construed as requiring that its operations beperformed in a specific order. Accordingly, where a method claim doesnot actually recite an order to be followed by its operations or it isnot otherwise specifically stated in the claims or descriptions that theoperations are to be limited to a specific order, it is in no wayintended that an order be inferred, in any respect. This holds for anypossible non-express basis for interpretation, including: matters oflogic with respect to arrangement of operations or operational flow;plain meaning derived from grammatical organization or punctuation; thenumber or type of embodiments described in the specification.

It will be apparent to those skilled in the art that variousmodifications and variations can be made without departing from thescope or spirit. Other embodiments will be apparent to those skilled inthe art from consideration of the specification and practice disclosedherein. It is intended that the specification and examples be consideredas exemplary only, with a true scope and spirit being indicated by thefollowing claims.

What is claimed is:
 1. A computing system, comprising: at least oneprocessor; and at least one memory device having processor-executableinstructions stored thereon that, in response to execution by the atleast one processor, cause the computing system to: receive prescriptiondata identifying one or more amounts of respective medications;generate, using the prescription data, an estimate of weight of apackage containing the one or more amounts of the respectivemedications; cause, at a time before automated packing of the respectivemedications into the package, a second computing system to provideshipping data for the package, wherein the shipping data comprises firstdata defining a shipping label, and wherein the second computing systemis remotely located relative to the computing system; receive theshipping data at a second time before the automated packing of therespective medications into the package; and store the shipping data ina storage device.
 2. The computing system of claim 1, the at least onememory device having further processor-executable instructions storedthereon that in response to execution by the at least one processorfurther cause the computing system to, receive, at a third time afterthe automated packing of the respective medications into the package iscomplete, a notification that the package is verified for shipping; andaccess the shipping data from the storage device.
 3. The computingsystem of claim 2, the at least one memory device having furtherprocessor-executable instructions stored thereon that in response toexecution by the at least one processor further cause the computingsystem to cause a printing device to output the shipping label.
 4. Thecomputing system of claim 1, wherein causing a second computing systemto provide shipping data for the package comprises, establishing a callsession with the second computing system; and sending, via the callsession, a query message for the shipping data to the second computingsystem, the query message comprising payload data identifying shippingattributes corresponding to the delivery package.
 5. The computingsystem of claim 4, wherein the shipping attributes comprise a firstattribute identifying the estimate of the weight of the deliverypackage, a second attribute identifying the respective medications, anda third attribute identifying a shipping address.
 6. The computingsystem of claim 1, wherein generating, using the prescription data, theestimate of the weight of a package comprises, identifying a receptacleto fit a first amount of the one or more amounts of respectivemedications; determining a weight of the identified receptacle byaccessing a database including a catalogue of receptacles.
 7. Thecomputing system of claim 6, wherein the generating further comprisesdetermining a weight of the first amount of the one or more amounts ofrespective medications.
 8. The computing system of claim 7, wherein thegenerating further comprises adding a weight of the package, the weightof the identified receptacle, and the weight of the first amount of theone or more amounts of respective medications.
 9. A method, comprising:receiving, by a dispensing pharmacy system, prescription dataidentifying one or more amounts of respective medications; generating,by the dispensing pharmacy system, using the prescription data, anestimate of weight of a package containing the one or more amounts ofthe respective medications; causing, by the dispensing pharmacy system,at a time before automated packing of the respective medications intothe package, a second computing system to provide shipping data for thepackage, wherein the shipping data comprises first data defining ashipping label, and wherein the second computing system is remotelylocated relative to the dispensing pharmacy system; receiving theshipping data by the dispensing pharmacy system at a second time beforeautomated packing of the respective medications into the package; andstoring, by the dispensing pharmacy system, the shipping data in astorage device.
 10. The method of claim 9, further comprising,receiving, by the computing system, at a third time after the automatedpacking of the respective medications into the package is complete, anotification that the package is verified for shipping; and accessing,by the computing system, the shipping data from the storage device. 11.The method of claim 10, further comprising causing, by the computingsystem, a printing device to output the shipping label.
 12. The methodof claim 9, wherein the causing comprises, establishing a call sessionwith the second computing system; and sending, via the call session, aquery message for the shipping data to the second computing system, thequery message comprising payload data identifying shipping attributescorresponding to the package.
 13. The method of claim 12, wherein theshipping attributes comprise a first attribute identifying the estimateof the weight of the package, a second attribute identifying therespective medications, and a third attribute identifying a shippingaddress.
 14. The method of claim 9, wherein the generating comprises,identifying a receptacle to fit a first amount of the one or moreamounts of respective medications; determining a weight of theidentified receptacle by accessing a database including a catalogue ofreceptacles.
 15. The method of claim 14, wherein the generating furthercomprises determining a weight of the first amount of the one or moreamounts of respective medications.
 16. The method of claim 15, whereinthe generating further comprises adding a weight of the package withoutprescribed content, the weight of the identified receptacle, and theweight of the first amount of the one or more amounts of respectivemedications.
 17. At least one computer-readable non-transitory storagemedium having processor-executable instructions stored thereon that, inresponse to execution, cause a computing system to: receive prescriptiondata identifying one or more amounts of respective medications;generate, using the prescription data, an estimate of weight of apackage containing the one or more amounts of the respectivemedications; cause, at a time before automated packing of the respectivemedications into the package, a second computing system to provideshipping data for the package, wherein the shipping data comprises firstdata defining a shipping label, and wherein the second computing systemis remotely located relative to the dispensing pharmacy system; receivethe shipping data; and store the shipping data in a storage device. 18.The at least one computer-readable non-transitory storage medium ofclaim 17, wherein the processor-executable instructions, in response tofurther execution, further cause the computing system to, receive, at asecond time after the automated packing of the respective medicationsinto the package is complete, a notification that the package isverified for shipping; and access the shipping data from the storagedevice.
 19. The at least one computer-readable non-transitory storagemedium of claim 18, the at least one memory device having furtherprocessor-executable instructions stored thereon that in response toexecution by the at least one processor further cause the computingsystem to cause a printing device to output the shipping label.
 20. Theat least one computer-readable non-transitory storage medium of claim17, wherein causing the second computing system to provide the shippingdata for the package comprises, establishing a call session with thesecond computing system; and sending, via the call session, a querymessage for the shipping data to the second computing system, the querymessage comprising payload data identifying shipping attributescorresponding to the delivery package.